huabulengdeng Goto Github PK

3rd-year-project

An Integrated ANN Multi-agent system for Energy Demand Management

algorithms_mathmodels

【国赛】【美赛】数学建模相关算法 MATLAB实现

autonomous-energy-controller-rl

Deep reinforcement learning for autonomous energy management

chpsoftware

combined-heat-and-power-system-economic-dispatch

Deep reinforcement learning approaches for CHP system economic dispatch

d3hre

Data Driven Dynamic Hybrid Renewable Energy design and simulation framework

data-for-robust-planning-of-iehs

Data for Robust planning of IEHS

data_ies_case

This is the data of an integrated energy system case.

densitypeakcluster

Python Code For 'Clustering By Fast Search And Find Of Density Peaks' In Science 2014.

dispatchtable

Code to optimally dispatch grid energy storage devices subject to user-specified constraints. Example data files provided.

distributed_smartgrid_algorithms

Implementation of 3 Proposed Consensus Based Economic Dispatch Optimization Algorithms

drl-for-microgrid-energy-management

We study the performance of various deep reinforcement learning algorithms for the problem of microgrid’s energy management system. We propose a novel microgrid model that consists of a wind turbine generator, an energy storage system, a population of thermostatically controlled loads, a population of price-responsive loads, and a connection to the main grid. The proposed energy management system is designed to coordinate between the different sources of flexibility by defining the priority resources, the direct demand control signals and the electricity prices. Seven deep reinforcement learning algorithms are implemented and empirically compared in this paper. The numerical results show a significant difference between the different deep reinforcement learning algorithms in their ability to converge to optimal policies. By adding an experience replay and a second semi-deterministic training phase to the well-known Asynchronous advantage actor critic algorithm, we achieved considerably better performance and converged to superior policies in terms of energy efficiency and economic value.

economic-load-dispatch-using-genetic-algorithm

An efficient optimization procedure based on genetic algorithm for the solution of economic load dispatch

energy_management_system

energy management system for the microgrid

energyplus-co-simulation-toolbox

Simulate runtime binded EnergyPlus models from Matlab/Simulink.

geosciences_exploration

Practical skills in areas such as data analysis, regressions, optimization, spectral analysis, differential equations, image analysis, computational statistics, and Monte Carlo simulations. Emphasis is on scientific and engineering applications.

heat-power-plant-reinforcement-learning-experiment

RL in Energy Space

integrated-energy-systems-with-caes

The optimal dispatch of CAES in the integrated energy systems

loadpredicting

AARIMA,K-MEANS,DBN,FFNN,GBRT,LSTM,RFR,SEQ2SEQ,SVR,XGBOOST

microgridoptimaldispatch

multi-agent-rl-energy-management

multivariate-time-series-data

nempy

A flexible tool kit for modelling Australia's National Electricity Market dispatch procedure.

online-recurrent-extreme-learning-machine

Online-Recurrent-Extreme-Learning-Machine (OR-ELM) for time-series prediction, implemented in python

opem

OPEM (Open Source PEM Fuel Cell Simulation Tool)

ph.d-thesis-on-caes

All materials associated with my Ph.D. thesis, titled 'Research on Flexibility Modeling and Operation of Advanced Adiabatic Compressed Air Energy Storage at Source-Grid-Load Side'. 博士论文：源-网-荷先进绝热压缩空气储能灵活性建模及运行研究

power-systems-optimization

Implementation of Optimization Techniques for Economic Dispatch of Power Systems

renewables_scenario_gen_gan

The implementation of scenario generation for renewables production process

res_nuc

French electricity sector dispatch model for renewable electricity resources and nuclear energy

rl-energy-management